



TileDB Vector Search is a scalable open-source vector database that stores and performs approximate nearest neighbor searches on high-dimensional dense and sparse vectors using TileDB's multi-dimensional array storage for petabyte-scale data. Key features include Vamana graph and IVF-PQ indexing, metadata filtering, multi-tenancy, serverless scalability on object stores like S3, and APIs in Python/C++ with gRPC support. Suited for RAG pipelines, recommendation systems, and anomaly detection; excels in sparse vector efficiency and cost savings compared to Milvus or Pinecone, while scaling better than Faiss for large production deployments.
Loading more......
On this page
TileDB Vector Search
TileDB Vector Search is a vector search solution leveraging the TileDB array storage format for high-performance similarity search.
MIT License.
Free and open-source.
Explore more items related to this one